Updating protection sets in a geographically distributed storage environment

ABSTRACT

In one or more embodiments described herein, system, method, and/or computer program products that facilitate updating degraded data protection sets in a geographically distributed storage system. According to an embodiment, a method can comprise receiving, by a system comprising a processor and a memory, a request to update a protection set for a first coded chunk in response to detecting deletion of a primary data chunk, wherein the first coded chunk and the primary data chunk are stored in a geographically distributed data storage system. The method can comprise generating, by the system, a transformation data chunk utilizing a secondary data chunk stored in the geographically distributed data storage system. The method can further comprise generating, by the system, a second coded chunk having an updated protection set, wherein the updated protection set is generated utilizing the transformation data chunk.

TECHNICAL FIELD

The subject disclosure relates generally to storage systems. Morespecifically, this disclosure relates to various embodiments forupdating of protection sets in a geographically distributed storageenvironment.

BACKGROUND

The large increase in amount of data generated by digital systems hascreated a new set of challenges for data storage environments.Traditional storage area network (SAN) and/or network-attached storage(NAS) architectures have not been designed to support data storageand/or protection at large multi-petabyte capacity levels. Objectstorage technology can be utilized to meet these requirements. Byutilizing object storage technology, organizations can not only keep upwith rising capacity levels, but can also store these new capacitylevels at a manageable cost point.

Typically, a scale-out, cluster-based, shared-nothing object storagethat employs a microservices architecture pattern, for example, an ECS™(formerly known as Elastic Cloud Storage) can be utilized as a storageenvironment for a new generation of workloads. ECS™ utilizes the latesttrends in software architecture and development to achieve increasedavailability, capacity use efficiency, and performance. ECS™ uses aspecific method for disk capacity management, wherein disk space ispartitioned into a set of blocks of fixed size called chunks. User datais stored in these chunks and the chunks are shared. One chunk cancomprise fragments of several user objects. Chunk content is modified inan append mode. When chunks become full, they are sealed and the contentof sealed chunks is immutable. Oftentimes, chunks can comprise a reducedset of data fragments. This increases capacity overheads on dataprotection and there are some cases when the overheads may beunreasonably high.

The above-described background relating to ECS™ is merely intended toprovide a contextual overview of some current issues, and is notintended to be exhaustive. Other contextual information may becomefurther apparent upon review of the following detailed description.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 illustrates an example cloud data storage system comprising thatfacilitates combining erasure-coded protection sets during meta chunkgeneration, according to one or more example implementations.

FIG. 2 illustrates an example layout of a chunk within an object storagesystem in accordance with an aspect of the specification.

FIG. 3 illustrates an example of a geographically distributed storagesystem accordance with one or more embodiments described herein.

FIG. 4 illustrates an example of a geographically distributed storagesystem accordance with one or more embodiments described herein.

FIG. 5 illustrates an example of a geographically distributed storagesystem accordance with one or more embodiments described herein.

FIG. 6 illustrates an example of a geographically distributed storagesystem accordance with one or more embodiments described herein.

FIG. 7 illustrates an example of a geographically distributed storagesystem accordance with one or more embodiments described herein

FIG. 8 illustrates an example of a chunk manager operational in ageographically distributed storage system accordance with one or moreembodiments described herein.

FIG. 9 illustrates an example of a chunk manager operational in ageographically distributed storage system accordance with one or moreembodiments described herein.

FIG. 10 depicts a diagram of an example, non-limiting computerimplemented method that facilitates efficient updating of dataprotection set in geographically distributed storage system.

FIG. 11 depicts a diagram of an example, non-limiting computerimplemented method that facilitates efficient updating of dataprotection set in geographically distributed storage system.

FIG. 12 illustrates a block diagram of an example computer operable toexecute updating data protection set in a geographically distributedstorage system.

DETAILED DESCRIPTION

One or more embodiments are now described with reference to thedrawings, wherein like reference numerals are used to refer to likeelements throughout. In the following description, for purposes ofexplanation, numerous specific details are set forth in order to providea thorough understanding of the various embodiments. It may be evident,however, that the various embodiments can be practiced without thesespecific details, e.g., without applying to any particular networkedenvironment or standard. In other instances, well-known structures anddevices are shown in block diagram form in order to facilitatedescribing the embodiments in additional detail.

The term “cloud” as used herein can refer to a cluster of nodes (e.g.,set of network servers), for example, within a distributed objectstorage system, that are communicatively and/or operatively coupled toeach other, and that host a set of applications utilized for servicinguser requests. In general, the cloud computing resources can communicatewith user devices via most any wired and/or wireless communicationnetwork to provide access to services that are based in the cloud andnot stored locally (e.g., on the user device). A typical cloud-computingenvironment can include multiple layers, aggregated together, thatinteract with each other to provide resources for end-users.

Example systems and methods disclosed herein, in one or moreembodiments, relate to cloud storage systems that utilize erasure codingfor data protection, such as, but not limited to an ECS™ platform. TheECS™ platform combines the cost advantages of commodity infrastructurewith the reliability, availability and serviceability of traditionalarrays. ECS™ uses erasure coding approach to protect user data. Witherasure coding, a data portion (D) is divided into k fragments. Duringencoding operation redundant m coding fragments are created. In anaspect, encoding assures that the system can tolerate the loss of any mfragments. In an embodiment, k data fragments and m coding fragmentscreated for a single data portion form a protection set. In one aspect,the ECS™ platform can comprise a cluster of nodes (also referred to as“cluster” herein) that delivers scalable and simple public cloudservices with the reliability and/or control of a private-cloudinfrastructure. Moreover, the ECS™ platform comprises a scale-out,cluster-based, shared-nothing object storage, which employs amicroservices architecture pattern. The ECS™ platform can supportstorage, manipulation, and/or analysis of unstructured data on a massivescale on commodity hardware. As an example, ECS™ can support mobile,cloud, big data, content-sharing, and/or social networking applications.ECS™ can be deployed as a turnkey storage appliance or as a softwareproduct that can be installed on a set of qualified commodity serversand/or disks. The ECS™ scale-out and geo-distributed architecture is acloud platform that can provide at least the following features: (i)lower cost than public clouds; (ii) unmatched combination of storageefficiency and data access; (iii) anywhere read/write access with strongconsistency that simplifies application development; (iv) no singlepoint of failure to increase availability and performance; (v) universalaccessibility that eliminates storage silos and inefficient extract,transform, load (ETL)/data movement processes; etc.

In an aspect, ECS™ does not rely on a file system for disk capacitymanagement. Instead, ECS™ partitions disk space into a set of blocks offixed size called chunks (e.g., having a chunk size of 128 MB). All userdata is stored in these chunks and the chunks are shared. Typically, achunk can comprise fragments of several different user objects. Thechunk content can be modified in an append-only mode. When a chunkbecomes full, it can be sealed and the content of a sealed chunk isimmutable. Further, ECS™ does not employ traditional data protectionschemes like mirroring or parity protection. Instead, ECS™ utilizeserasure coding for data protection. A chunk can be divided into indexedportions (e.g., data fragments), for example, by a chunk manager. Anindex of a data fragment can be a numerical value assigned by the chunkmanager and utilized for erasure coding. Moreover, the index of a datafragment can be utilized to determine a coefficient, within an erasurecoding matrix (e.g., the index can be utilized to determine a row and/orcolumn of the matrix), which is to be combined (e.g., multiplied) withthe data fragment to generate a corresponding coding fragment for thechunk. In an aspect, ECS™ is a cloud storage that supportsgeographically distributed setups consisting of two or more zones. Thecorresponding feature is called GEO. GEO can be used to provide anadditional protection of user data by means of replication. Thereplication mechanism works at the chunks level. ECS may use GEO erasurecoding technique to minimize capacity overhead associated with GEO dataprotection. Although the systems and methods disclosed herein have beendescribed with respect to object storage systems (e.g., ECS™), it isnoted that the subject specification is not limited to object storagesystems and can be utilized for most any storage systems that utilizeerasure coding for data protection and chunks for disk capacitymanagement. Thus, any of the embodiments, aspects, concepts, structures,functionalities or examples described herein are non-limiting, and thetechnology may be used in various ways that provide benefits andadvantages in computing and data storage in general.

Oftentimes erasure-coded storage systems create a data protection unit(e.g., meta chunk), which combines two or more source chunks having areduced sets of data fragments, to increase capacity use efficiencywithout verification and data copying. However, generation of this dataprotection unit requires complete data re-protection. In other words, anencoding operation (e.g., erasure coding operation) has to be performedusing all/combined data fragments of the meta chunk to generate newcoding fragments. This is a very resource-demanding operation,especially for GEO erasure coding. There are situations when aprotection set created with GEO erasure coding has fewer than k datachunks. For example, deletion of data chunks leads to a situation when aGEO protection set contains fewer than k data chunks. We call suchprotection sets degraded. When data is protected with erasure coding,the overheads on data protection may be calculated as m/k. In thesituation when there are fewer data chunks (l) the equation to use tocalculate the overheads is m/l. The fewer l the greater capacityoverheads on data protection and there are cases when the overheads maybe unreasonably high. To reduce system capacity overheads on dataprotection, meta chunks can be used. Meta chunks unite (e.g., sum up)two or more degraded protection sets into a meta protection set andprotect data at the meta protection set level. This can create a lessdegraded protection set or even a protection set of full value with anumber of data chunks close to or 1 equal to k. In an aspect, a completere-protection is performed upon creation of meta protection set. There-protection can be achieved without difficulty when two or more dataprotection sets complement each other. Their protection sets can beunited into a greater protection set via simple summing up operation. Itis enough to sum up coding chunks of subsidiary protection sets to getcoding chunks of a greater (meta) protection set. In situations wherethe data protection sets are not complementary, various techniques canbe implemented to make a non-complementary protection setscomplementary. When converting a non-complementary protection setscomplementary, all coding chunks in the connected zones need to beupdated. This increases inter-zone network traffic for GEO setups. Thesystems and methods disclosed herein facilitate a resource-efficientmethod to update degraded data protection set that reduces inter-zonenetwork traffic in geographically distributed storage systems.

In an embodiment, where there are two zones, of two or more zonessystem, maintain data protection sets (e.g., a meta coded chunk), atleast one zone maintains data protection set (e.g., P chunk) calculatedusing an XOR (e.g., ‘exclusive or’ convolution of chunks, hereinafterreferenced as XOR, ‘⊕’) operation. In an embodiment, the other zonesthat maintain the data protection set (e.g., Q chunk), can utilizevarious techniques, for example, but not limited to a general GaloisField (GF) arithmetic to calculate the data protection set thatminimizes storage overhead. The advantage of using an XOR operation isthat the chunk's position is not relevant and therefore no requirementto modify the index position to combine (e.g., no need to changenon-complementary data protection set to complementary data protectionset). Using XOR operation, new chunks can be appended to an existing Pchunk and easily extracted from P chunk. In addition, when a data chunkbecomes degraded, as discussed above, the P chunk (e.g., formed used theXOR operation) need not require any inter-zone network traffic to beupdated, because P chunk formed using an XOR operation does not requirean update. In an embodiment, only the Q chunk needs to be updated. Thus,although the degraded chunk was maintained at two zones, only one zonewill require an update to the data protection set.

In an exemplary embodiment, a geographically distributed storageenvironment comprises six zone that store and protect data. In someembodiments, 4 zones comprise data chunks and 2 zones comprise backup inform of coding chunks, one using an XOR operation to generate the codingchunk (chunk P) and one using a standard technique (e.g., GF arithmeticor Geo erasure coding) to generate the coding chunk (chunk Q). When adata chunk is deleted, the protection set becomes degraded (e.g., chunkQ is considered degraded since resource space is allocated for a deletedchunk). In an embodiment, when deletion of data chunk is detected (e.g.,a data set is degraded), the system can update the degraded protectionset by combining the degraded data protection set with a complementarydata protection set. According the embodiment, combination with anothercomplementary data protection set is required only for the chunk Q. Forchunk P a XOR operation is performed to remove the empty portion (e.g.,space previously occupied by deleted chunk). If the degraded protectionset is not complementary, the system can modify the index of one or morechunks to make the degraded data protection set complementary withanother data protection set. In an embodiment, a data chunk from any oneof the zones comprising a data chunk, a transformation chunk can becreated to adjust the index position of the selected data chunk. Thetransformation chunk can be transformed (e.g., transmitted, inter-zonenetwork transmission, etc.) to zone comprising the chunk Q, wherein thetransformation chunk can be combined (e.g., using summing, unite or XORoperation to combine) with the chunk Q to adjust the index position ofselected data chunk. Upon generating a data protection set with anupdated index position of the selected data chunk, the degraded dataprotection set is updated. Thus, updating the degraded data protectionset via shifting the index and performing an XOR operation, all thedegraded protection sets can be re-protected with minimum inter-zonenetwork traffic.

To the accomplishment of the foregoing and related ends, the disclosedsubject matter, then, comprises one or more of the features hereinaftermore fully described. The following description and the annexed drawingsset forth in detail certain illustrative aspects of the subject matter.However, these aspects are indicative of but a few of the various waysin which the principles of the subject matter can be employed. Otheraspects, advantages, and novel features of the disclosed subject matterwill become apparent from the following detailed description whenconsidered in conjunction with the provided drawings.

FIG. 1 shows part of a cloud data storage system such as ECS™ comprisinga zone (e.g., cluster) 102 of storage nodes 104(1)-104(M), in which eachnode is typically a server configured primarily to serve objects inresponse to client requests (e.g., received from clients 108). The nodes104(1)-104(M) can be coupled to each other via a suitable datacommunications link comprising interfaces and protocols such as, but notlimited to, Ethernet block 106.

Clients 108 can send data system-related requests to the cluster 102,which in general is configured as one large object namespace; there maybe on the order of billions of objects maintained in a cluster, forexample. To this end, a node such as the node 104(2) generally comprisesports 112 by which clients connect to the cloud storage system. Exampleports are provided for requests via various protocols, including but notlimited to SMB (server message block), FTP (file transfer protocol),HTTP/HTTPS (hypertext transfer protocol), and NFS (Network File System);further, SSH (secure shell) allows administration-related requests, forexample.

Each node, such as the node 104(2), includes an instance of an objectstorage system 114 and data services. For a cluster that comprises a“GEO” zone of a geographically distributed storage system, at least onenode, such as the node 104(2), includes or coupled to reference trackingasynchronous replication logic 116 that synchronizes the cluster/zone102 with each other remote GEO zone 118. Note that ECS™ implementsasynchronous low-level replication, that is, not object levelreplication. Typically, organizations protect against outages orinformation loss by backing-up (e.g., replicating) their dataperiodically. During backup, one or more duplicate or deduplicatedcopies of the primary data are created and written to a new disk or to atape, for example within a different zone. The term “zone” as usedherein can refer to one or more clusters that is/are independentlyoperated and/or managed. Different zones can be deployed within the samelocation (e.g., within the same data center) and/or at differentgeographical locations (e.g., within different data centers).

In general, and in one or more implementations, e.g., ECS™, disk spaceis partitioned into a set of large blocks of fixed size called chunks;user data is stored in chunks. Chunks are shared, that is, one chunk maycontain segments of multiple user objects; e.g., one chunk may containmixed segments of some number of (e.g., three) user objects.

A chunk manager 120 can be utilized to manage the chunks and theirprotection (e.g., via erasure coding (EC)). Erasure coding was createdas a forward error correction method for binary erasure channel.However, erasure coding can be used for data protection on datastorages. During erasure coding (e.g., utilizing a k+m configuration),the chunk manager 120 can partition a piece of data (e.g., chunk) into kdata fragments of equal size. During encoding, redundant m codingfragments are created so that the system can tolerate the loss of any mfragments. Typically, the chunk manager 120 can assign indices to thedata fragments (and corresponding coding fragments). In an example, anindex can be a numerical value (e.g., 1 to k) that is utilized forerasure coding. Moreover, the index of a data fragment can be utilizedto determine a coefficient, within an erasure coding matrix, which is tobe combined (e.g., multiplied) with the data fragment to generate acorresponding coding fragment for the chunk. For example, an index valuecan specify a row and/or column of the coefficient within the erasurecoding matrix. As an example, the indices can be assigned based on adefined sequence, in a random order, based on a defined criterion (e.g.,to increase probability of complementary data fragments), based onoperator preferences, etc. The process of coding fragments creation iscalled encoding. The process of data fragments recovery using availabledata and coding fragments is called decoding.

In one example embodiment, GEO erasure coding can also be utilized,wherein if a distributed storage 100 is to tolerate the loss of any mzones/clusters/chunks, then GEO erasure coding can begin at each zone byreplicating each new chunk to at least m remote zones. As a result,there are m backup copies of each chunk. Typically, there is one primarybackup copy, which can be utilized for encoding. Encoding is performedby one zone for primary backup chunks and other zones replicate to it.Once a zone has k primary chunks replicated from different remote zones,the zone can perform encoding using the chunks replicated to it as datafragments. The chunk size is fixed, in ECS™, with padding or other datato complement, wherein the other data is added as needed. The result ofencoding is m data portions of a chunk size. They are stored as chunksof a specific type called coding chunks. After encoding is complete, thezone can store one coding chunk locally and move other m−1 coding chunksto remote zones making sure all the k+m data and coding chunks arestored at different zones whenever possible. Afterwards, the primarybackup chunks used for encoding and their peer backup chunks at otherzones can be deleted.

In some embodiments, the chunk manager 120 can efficiently generatecombined data protection sets during consolidating two or moreerasure-coded data portions (e.g., normal/source chunks) that have areduced sets of data fragments. As an example, chunk manager 120 canverify that the two or more erasure-coded data portions arecomplementary (e.g., do not have data fragments with the same index) andperform a summing operation to combine their corresponding codingfragments to generate a combined protection set. A CPU 122 and RAM 124are shown for completeness; note that the RAM 124 can comprise at leastsome non-volatile RAM. The node includes storage devices such as disks126, comprising hard disk drives and/or solid-state drives. It is notedthat the storage devices can comprise volatile memory(s) or nonvolatilememory(s), or both volatile and nonvolatile memory(s). Examples ofsuitable types of volatile and non-volatile memory are described belowwith reference to FIG. 12. The memory (e.g., data stores, databases,tables, etc.) of the subject systems and methods is intended tocomprise, without being limited to, these and any other suitable typesof memory.

FIG. 2 illustrates an example layout 200 of a chunk within an objectstorage system in accordance with an aspect of the specification. In anaspect, disk space of the object storage system can be partitioned intoa set of blocks of fixed size called chunks. As an example, the chunksize can be 128 MB. Typically, user data is stored in these chunks andthe chunks are shared. As shown in FIG. 2, a chunk 202 can comprisesegments of several user objects (e.g., object 1 segments 204, object 2segments 206, and object 3 segments 208). It is noted that the chunklayout depicted in FIG. 2. is one example and the chunks can have mostany other layout with segments from one or more user objects. Chunkcontent is modified in an append-only mode. When the chunk becomes fullenough, it is sealed. After the chunk is sealed, its content isimmutable.

In an aspect, the chunk can be protected by employing erasure coding.During erasure coding, a chunk can be divided into k data fragments ofequal size. To encode the chunk, redundant m coding fragments arecreated so that the system can tolerate the loss of any m fragments. Theprocess of generating the coding fragments is called encoding. Theprocess of data fragments recovery using available data and codingfragments is called decoding. As an example, the encoding operation canbe represented with the equation below:

C _(i)=Σ_(j=1) ^(k) C _(i,j)  (1)

wherein,

C _(i,j) =X _(i,j) *D _(j)  (2)

and wherein, X_(i,j) is a defined coefficient from a coding matrix(e.g., wherein i, j, and/or k can be most any integer). Further, j is anindex assigned to the data fragment. It is noted that D_(j) areindependent data fragments and C_(i) are coding fragments.

Additionally, or optionally, the systems and methods disclosed hereincan support geographically distributed setups (GEO) comprising two ormore zones. GEO can be used to provide an additional protection of userdata by means of replication. Replication works at the chunk level,wherein a backup copy of a chunk stored in a primary zone can bereplicated to one or more secondary zones. Each zone protects the chunksit stores. If a copy of a chunk becomes unavailable, it can be recoveredusing its other copy. This process is called GEO recovery. In case ofGEO erasure coding, remote backup copies of data chunks are used as datafragments and coding fragments created for such data fragments arestored as coding chunks.

FIG. 3 illustrates an example of a geographically distributed storagesystem 300 accordance with one or more embodiments described herein.Repetitive description of like elements employed in respectiveembodiments is omitted for sake of brevity. According to someembodiments, the geographically distributed storage system 300 caninclude one or more zones (e.g., six zones) 312 a, . . . , 312 finterconnected to each other through the cloud 302, wherein zones 312 a,. . . , 312 d (e.g., zones 1-4) each comprises data chunks 352 a, . . ., 352 d, respectively, zone 312 e (e.g., zone 5) comprise a dataprotection set (e.g., coding chunk P, 352 e) and zone 312 f (e.g., zone6) comprise a data protection set (e.g., coding chunk Q, 352 f). In someembodiments, the coding chunk P 352 e is calculated using an XORoperation (A⊕B⊕C⊕D=>ABCD) and the coding chunk Q 352 f is calculatedusing a GEO erasure coding method for creating a meta chunk wherein thedata chunks 352 a, . . . , 352 d, are in specific order (e.g., ABCD). Insome embodiments, the coding chunk Q 352 f is calculated using GFarithmetic.

FIG. 4 illustrates an example of a geographically distributed storagesystem 400 accordance with one or more embodiments described herein.Repetitive description of like elements employed in respectiveembodiments is omitted for sake of brevity. According to someembodiments, as it happens often, data chunk D 352 d has been deletedfrom zone 4 312 d. The deletion of data chunk D 352 d causes zone 6 312f to become degraded since the data chunk D 352 d is no longer availablefor data protection. This is illustrated as coding chunk Q comprising“ABC_”, wherein “_” denotes the missing data chunk D 352 d. It should benoted that chunk P 352 e in not considered degraded because it is merelythe XOR of the data chunks (e.g., A⊕B ⊕C=>ABC). The overhead has beenincreased at zone 6 312 f since the data protection is contains storagespace for a deleted data chunk (e.g., “_”). Thus, a task can beinitiated by system to adjust placement of a chunk (e.g., change theindex position of C from 3 to 4) in order to re-protect the dataprotection set.

FIG. 5 illustrates an example of a geographically distributed storagesystem 500 accordance with one or more embodiments described herein.Repetitive description of like elements employed in respectiveembodiments is omitted for sake of brevity. According to someembodiments, the system (e.g., the chunk manger 120) can request zone 3312 c comprising chunk C 352 c to generate a transformation chunk 352 tusing chunk C 352 c and (X_(Q,4)−X_(Q,3)) arithmetic. The transformationchunk T 352 t can be used change index position of ‘C’ (representingchunk C 352 c) in the coding chunk Q 352 f from 3^(rd) position to4^(th).

FIG. 6 illustrates an example of a geographically distributed storagesystem 600 accordance with one or more embodiments described herein.Repetitive description of like elements employed in respectiveembodiments is omitted for sake of brevity. According to someembodiments, the transformation chunk T 352 t is transmitted to zone 6312 f. Using a standard combining technique, the transformation chunk T352 t is combined with chunk Q 352 f to generate a new coding chunk Q′352 f′ (e.g., AB_C). Upon combining the chunk Q 352 f withtransformation chunk T 352 t, the index position of ‘C’ is changed from3^(rd) position to 4^(th) position in the new data protection set.

FIG. 7 illustrates an example of a geographically distributed storagesystem 700 accordance with one or more embodiments described herein.Repetitive description of like elements employed in respectiveembodiments is omitted for sake of brevity. According to someembodiments, the transformation chunk T 352 t is removed from zone 3 312c and the chunk Q 352 f is replaced by new coding chunk Q′ 352 f′ (e.g.,AB_C). It should be noted that only one inter-zone network transmissionoccurred for updating the chunk Q 352 f and no transmission was requiredto update chunk P 352 e.

FIG. 8 illustrates an example of a chunk manager 802 operational in ageographically distributed storage system 800 accordance with one ormore embodiments described herein. Repetitive description of likeelements employed in respective embodiments is omitted for sake ofbrevity. In some embodiments, the chunk manager 802 comprises a chunkdeletion detection component 810 that detects when a data chunk withingeographically distributed storage system 800 has been deleted from azone (e.g., deletion of data chunk D 352 d of zone 4 312 d, discussedabove). A message, indicating deletion of a data chunk, can betransmitted via wired line or wirelessly to a controller (not shown)that may control functions of each zone. In some embodiments, controllercan request an update to the protection set for the coding chunk (e.g.,zone 6 312 f). In some embodiments, the chunk manager 802 can comprise atransformation component 812 that generates a transformation data chunk(e.g., transformation chunk 352 t) using chunk C 352 c stored in zone 3312 c. In and embodiment, once the transformation data chunk isgenerated, the transformation chunk is transmitted to zone 6 352 f. Insome embodiments, the chunk manager 802 can comprise a combine component814 that generates an updated coded chunk (e.g., chunk Q′ 352 f′) bycombining the chunk Q 352 f and the transformation chunk 352 t resultingin chunk Q′ 352 f′ having an updated protection set that is differentfrom original data protection set of chunk Q 352 f.

Aspects of the processor 806 can constitute machine-executablecomponent(s) embodied within machine(s), e.g., embodied in one or morecomputer readable mediums (or media) associated with one or moremachines. Such component(s), when executed by the one or more machines,e.g., computer(s), computing device(s), virtual machine(s), etc. cancause the machine(s) to perform the operations described herein. In anaspect, memory 804 can store computer executable components andinstructions. It is noted that the memory 804 can comprise volatilememory(s) or nonvolatile memory(s), or can comprise both volatile andnonvolatile memory(s). Examples of suitable types of volatile andnon-volatile memory are described below with reference to FIG. 12. Thememory (e.g., data stores, databases) of the subject systems and methodsis intended to comprise, without being limited to, these and any othersuitable types of memory. In some embodiments, the chunk manager 802 canreside in zone and communicatively coupled to one or more of theremaining zones.

FIG. 9 illustrates an example of the chunk manager 802 operational in ageographically distributed storage system 900 accordance with one ormore embodiments described herein. Repetitive description of likeelements employed in respective embodiments is omitted for sake ofbrevity. In some embodiments, the chunk manager 802 can comprises anupdate component 914 that updates the degraded coding chunk Q 352 f withnew coding chunk Q′ 352 f′ having updated data protection set. In someembodiments, the chunk manager 802 can comprise a cleanup component 916that removes the degraded coding chunk Q 352 f and the transformationchunk 352 t from zone 6 312 f.

FIG. 10 depicts a diagram of an example, non-limiting computerimplemented method that facilitates efficient updating of dataprotection set in geographically distributed storage system. Repetitivedescription of like elements employed in other embodiments describedherein is omitted for sake of brevity. In some examples, flow diagram1000 can be implemented by operating environment 1200 described below.It can be appreciated that the operations of flow diagram 1000 can beimplemented in a different order than is depicted.

In non-limiting example embodiments, a computing device (or system)(e.g., computer 1212) is provided, the device or system comprising oneor more processors and one or more memories that stores executableinstructions that, when executed by the one or more processors, canfacilitate performance of the operations as described herein, includingthe non-limiting methods as illustrated in the flow diagrams of FIG. 10.

Operation 1002 depicts determining if a primary data chunk was deleted.If a primary data chunk was deleted, then perform operation 1004.Otherwise, continue monitoring. Operation 1004 depicts receiving, by asystem comprising a processor and a memory, a request to update aprotection set for a first coded chunk in response to detecting deletionof a primary data chunk, wherein the first coded chunk and the primarydata chunk are stored in a geographically distributed data storagesystem. Operation 1006 depicts generating, by the system, atransformation data chunk utilizing a secondary data chunk stored in thegeographically distributed data storage system. Operation 1008 depictsgenerating, by the system, a second coded chunk having an updatedprotection set, wherein the updated protection set is generatedutilizing the transformation data chunk.

FIG. 11 depicts a diagram of an example, non-limiting computerimplemented method that facilitates efficient updating of dataprotection set in geographically distributed storage system. Repetitivedescription of like elements employed in other embodiments describedherein is omitted for sake of brevity. In some examples, flow diagram1100 can be implemented by operating environment 1200 described below.It can be appreciated that the operations of flow diagram 1100 can beimplemented in a different order than is depicted.

In non-limiting example embodiments, a computing device (or system)(e.g., computer 1212) is provided, the device or system comprising oneor more processors and one or more memories that stores executableinstructions that, when executed by the one or more processors, canfacilitate performance of the operations as described herein, includingthe non-limiting methods as illustrated in the flow diagrams of FIG. 11.

Operation 1102 depicts determining if a primary data chunk was deleted.If a primary data chunk was deleted, then perform operation 1104.Otherwise, continue monitoring. Operation 1104 depicts receiving, by asystem comprising a processor and a memory, a request to update aprotection set for a first coded chunk in response to detecting deletionof a primary data chunk, wherein the first coded chunk and the primarydata chunk are stored in a geographically distributed data storagesystem. Operation 1106 depicts generating, by the system, atransformation data chunk utilizing a secondary data chunk stored in thegeographically distributed data storage system. Operation 1108 depictsgenerating, by the system, a second coded chunk having an updatedprotection set, wherein the updated protection set is generatedutilizing the transformation data chunk. Operation 1110 depictstransforming, by the system, the transformation data chunk from thesecond zone to the third zone. Operation 1112 depicts updating, by thesystem, the first coded chunk with the second coded chunk. Operation1114 depicts deleting, by the system, the first coded chunk and thetransformation data chunk.

FIG. 12 illustrates a block diagram of an example computer operable toexecute updating data protection set in a geographically distributedstorage system. In order to provide additional context for variousaspects of the disclosed subject matter, FIG. 12 and the followingdiscussion are intended to provide a brief, general description of asuitable computing environment 1200 in which the various aspects of thespecification can be implemented. While the specification has beendescribed above in the general context of computer-executableinstructions that can run on one or more computers, those skilled in theart will recognize that the specification also can be implemented incombination with other program modules and/or as a combination ofhardware and software.

Generally, program modules include routines, programs, components, datastructures, etc., that perform particular tasks or implement particularabstract data types. Moreover, those skilled in the art will appreciatethat the inventive methods can be practiced with other computer systemconfigurations, including single-processor or multiprocessor computersystems, minicomputers, mainframe computers, as well as personalcomputers, hand-held computing devices, microprocessor-based orprogrammable consumer electronics, and the like, each of which can beoperatively coupled to one or more associated devices. The illustratedaspects of the specification can also be practiced in distributedcomputing environments where certain tasks are performed by remoteprocessing devices that are linked through a communications network. Ina distributed computing environment, program modules can be located inboth local and remote memory storage devices.

Computing devices typically include a variety of media, which caninclude computer-readable storage media and/or communications media,which two terms are used herein differently from one another as follows.Computer-readable storage media can be any available storage media thatcan be accessed by the computer and includes both volatile andnonvolatile media, removable and non-removable media. By way of example,and not limitation, computer-readable storage media can be implementedin connection with any method or technology for storage of informationsuch as computer-readable instructions, program modules, structureddata, or unstructured data. Computer-readable storage media can include,but are not limited to, RAM, ROM, EEPROM, flash memory or other memorytechnology, CD-ROM, digital versatile disk (DVD) or other optical diskstorage, magnetic cassettes, magnetic tape, magnetic disk storage orother magnetic storage devices, or other tangible and/or non-transitorymedia which can be used to store desired information. Computer-readablestorage media can be accessed by one or more local or remote computingdevices, e.g., via access requests, queries or other data retrievalprotocols, for a variety of operations with respect to the informationstored by the medium.

Communications media typically embody computer-readable instructions,data structures, program modules or other structured or unstructureddata in a data signal such as a modulated data signal, (e.g., a carrierwave or other transport mechanism), and includes any informationdelivery or transport media. The term “modulated data signal” or signalsrefers to a signal that has one or more of its characteristics set orchanged in such a manner as to encode information in one or moresignals. By way of example, and not limitation, communication mediainclude wired media, such as a wired network or direct-wired connection,and wireless media such as acoustic, radio frequency (RF), infrared andother wireless media.

With reference to FIG. 12, a block diagram of a computing system 1200operable to execute the disclosed systems and methods is illustrated, inaccordance with an embodiment. Computer 1212 comprises a processing unit1214, a system memory 1216, and a system bus 1218. As an example, thecomponent(s), server(s), client(s), node(s), cluster(s), system(s),zone(s), module(s), agent(s), engine(s), manager(s), and/or device(s)disclosed herein with respect to systems 400-900 can each include atleast a portion of the computing system 1200. System bus 1218 couplessystem components comprising, but not limited to, system memory 1216 toprocessing unit 1214. Processing unit 1214 can be any of variousavailable processors. Dual microprocessors and other multiprocessorarchitectures also can be employed as processing unit 1214.

System bus 1218 can be any of several types of bus structure(s)comprising a memory bus or a memory controller, a peripheral bus or anexternal bus, and/or a local bus using any variety of available busarchitectures comprising, but not limited to, industrial standardarchitecture (ISA), micro-channel architecture (MSA), extended ISA(EISA), intelligent drive electronics (IDE), VESA local bus (VLB),peripheral component interconnect (PCI), card bus, universal serial bus(USB), advanced graphics port (AGP), personal computer memory cardinternational association bus (PCMCIA), Firewire (IEEE 1394), smallcomputer systems interface (SCSI), and/or controller area network (CAN)bus used in vehicles.

System memory 1216 comprises volatile memory 1220 and nonvolatile memory1222. A basic input/output system (BIOS), comprising routines totransfer information between elements within computer 1212, such asduring start-up, can be stored in nonvolatile memory 1222. By way ofillustration, and not limitation, nonvolatile memory 1222 can compriseROM, PROM, EPROM, EEPROM, or flash memory. Volatile memory 1220comprises RAM, which acts as external cache memory. By way ofillustration and not limitation, RAM is available in many forms such asSRAM, dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rateSDRAM (DDR SDRAM), enhanced SDRAM (ESDRAM), Synchlink DRAM (SLDRAM),Rambus direct RAM (RDRAM), direct Rambus dynamic RAM (DRDRAM), andRambus dynamic RAM (RDRAM).

Computer 1212 also comprises removable/non-removable,volatile/non-volatile computer storage media. FIG. 12 illustrates, forexample, disk storage 1224. Disk storage 1224 comprises, but is notlimited to, devices like a magnetic disk drive, floppy disk drive, tapedrive, Jaz drive, Zip drive, LS-100 drive, flash memory card, or memorystick. In addition, disk storage 1224 can comprise storage mediaseparately or in combination with other storage media comprising, butnot limited to, an optical disk drive such as a compact disk ROM device(CD-ROM), CD recordable drive (CD-R Drive), CD rewritable drive (CD-RWDrive) or a digital versatile disk ROM drive (DVD-ROM). To facilitateconnection of the disk storage devices 1224 to system bus 1218, aremovable or non-removable interface is typically used, such asinterface 1226.

It is to be appreciated that FIG. 12 describes software that acts as anintermediary between users and computer resources described in suitableoperating environment 1200. Such software comprises an operating system1228. Operating system 1228, which can be stored on disk storage 1224,acts to control and allocate resources of computer system 1212. Systemapplications 1230 take advantage of the management of resources byoperating system 1228 through program modules 1232 and program data 1234stored either in system memory 1216 or on disk storage 1224. It is to beappreciated that the disclosed subject matter can be implemented withvarious operating systems or combinations of operating systems.

A user can enter commands or information into computer 1212 throughinput device(s) 1236. Input devices 1236 comprise, but are not limitedto, a pointing device such as a mouse, trackball, stylus, touch pad,keyboard, microphone, joystick, game pad, satellite dish, scanner, TVtuner card, digital camera, digital video camera, web camera, cellularphone, user equipment, smartphone, and the like. These and other inputdevices connect to processing unit 1214 through system bus 1218 viainterface port(s) 1238. Interface port(s) 1238 comprise, for example, aserial port, a parallel port, a game port, a universal serial bus (USB),a wireless based port, e.g., Wi-Fi, Bluetooth®, etc. Output device(s)1240 use some of the same type of ports as input device(s) 1236.

Thus, for example, a USB port can be used to provide input to computer1212 and to output information from computer 1212 to an output device1240. Output adapter 1242 is provided to illustrate that there are someoutput devices 1240, like display devices, light projection devices,monitors, speakers, and printers, among other output devices 1240, whichuse special adapters. Output adapters 1242 comprise, by way ofillustration and not limitation, video and sound devices, cards, etc.that provide means of connection between output device 1240 and systembus 1218. It should be noted that other devices and/or systems ofdevices provide both input and output capabilities such as remotecomputer(s) 1244.

Computer 1212 can operate in a networked environment using logicalconnections to one or more remote computers, such as remote computer(s)1244. Remote computer(s) 1244 can be a personal computer, a server, arouter, a network PC, a workstation, a microprocessor based appliance, apeer device, or other common network node and the like, and typicallycomprises many or all of the elements described relative to computer1212.

For purposes of brevity, only a memory storage device 1246 isillustrated with remote computer(s) 1244. Remote computer(s) 1244 islogically connected to computer 1212 through a network interface 1248and then physically and/or wirelessly connected via communicationconnection 1250. Network interface 1248 encompasses wire and/or wirelesscommunication networks such as local-area networks (LAN) and wide-areanetworks (WAN). LAN technologies comprise fiber distributed datainterface (FDDI), copper distributed data interface (CDDI), Ethernet,token ring and the like. WAN technologies comprise, but are not limitedto, point-to-point links, circuit switching networks like integratedservices digital networks (ISDN) and variations thereon, packetswitching networks, and digital subscriber lines (DSL).

Communication connection(s) 1250 refer(s) to hardware/software employedto connect network interface 1248 to bus 1218. While communicationconnection 1250 is shown for illustrative clarity inside computer 1212,it can also be external to computer 1212. The hardware/software forconnection to network interface 1248 can comprise, for example, internaland external technologies such as modems, comprising regular telephonegrade modems, cable modems and DSL modems, wireless modems, ISDNadapters, and Ethernet cards.

The computer 1212 can operate in a networked environment using logicalconnections via wired and/or wireless communications to one or moreremote computers, cellular based devices, user equipment, smartphones,or other computing devices, such as workstations, server computers,routers, personal computers, portable computers, microprocessor-basedentertainment appliances, peer devices or other common network nodes,etc. The computer 1212 can connect to other devices/networks by way ofantenna, port, network interface adaptor, wireless access point, modem,and/or the like.

The computer 1212 is operable to communicate with any wireless devicesor entities operatively disposed in wireless communication, e.g., aprinter, scanner, desktop and/or portable computer, portable dataassistant, communications satellite, user equipment, cellular basedevice, smartphone, any piece of equipment or location associated with awirelessly detectable tag (e.g., scanner, a kiosk, news stand,restroom), and telephone. This comprises at least Wi-Fi and Bluetooth®wireless technologies. Thus, the communication can be a predefinedstructure as with a conventional network or simply an ad hoccommunication between at least two devices.

The computing system 1200 is operable to communicate with any wirelessdevices or entities operatively disposed in wireless communication,e.g., desktop and/or portable computer, server, communicationssatellite, etc. This includes at least Wi-Fi and Bluetooth® wirelesstechnologies. Thus, the communication can be a predefined structure aswith a conventional network or simply an ad hoc communication between atleast two devices.

Wi-Fi, or Wireless Fidelity, allows connection to the Internet from acouch at home, a bed in a hotel room, or a conference room at work,without wires. Wi-Fi is a wireless technology similar to that used in acell phone that enables such devices, e.g., computers, to send andreceive data indoors and out; anywhere within the range of a basestation. Wi-Fi networks use radio technologies called IEEE 802.11 (a, b,g, n, etc.) to provide secure, reliable, fast wireless connectivity. AWi-Fi network can be used to connect computers to each other, to theInternet, and to wired networks (which use IEEE 802.3 or Ethernet).Wi-Fi networks operate in the unlicensed 5 GHz radio band at a 54 Mbps(802.11a) data rate, and/or a 2.4 GHz radio band at an 11 Mbps(802.11b), a 54 Mbps (802.11g) data rate, or up to a 600 Mbps (802.11n)data rate for example, or with products that contain both bands (dualband), so the networks can provide real-world performance similar to thebasic 12BaseT wired Ethernet networks used in many offices.

As it employed in the subject specification, the term “processor” canrefer to substantially any computing processing unit or devicecomprising, but not limited to comprising, single-core processors;single-processors with software multithread execution capability;multi-core processors; multi-core processors with software multithreadexecution capability; multi-core processors with hardware multithreadtechnology; parallel platforms; and parallel platforms with distributedshared memory in a single machine or multiple machines. Additionally, aprocessor can refer to an integrated circuit, a state machine, anapplication specific integrated circuit (ASIC), a digital signalprocessor (DSP), a programmable gate array (PGA) including a fieldprogrammable gate array (FPGA), a programmable logic controller (PLC), acomplex programmable logic device (CPLD), a discrete gate or transistorlogic, discrete hardware components, or any combination thereof designedto perform the functions described herein. Processors can exploitnano-scale architectures such as, but not limited to, molecular andquantum-dot based transistors, switches and gates, in order to optimizespace usage or enhance performance of user equipment. A processor mayalso be implemented as a combination of computing processing units. Oneor more processors can be utilized in supporting a virtualized computingenvironment. The virtualized computing environment may support one ormore virtual machines representing computers, servers, or othercomputing devices. In such virtualized virtual machines, components suchas processors and storage devices may be virtualized or logicallyrepresented. In an aspect, when a processor executes instructions toperform “operations”, this could include the processor performing theoperations directly and/or facilitating, directing, or cooperating withanother device or component to perform the operations

In the subject specification, terms such as “data store,” data storage,”“database,” “cache,” and substantially any other information storagecomponent relevant to operation and functionality of a component, referto “memory components,” or entities embodied in a “memory” or componentscomprising the memory. It is noted that the memory components, orcomputer-readable storage media, described herein can be either volatilememory or nonvolatile memory, or can include both volatile andnonvolatile memory. By way of illustration, and not limitation,nonvolatile memory can include read only memory (ROM), programmable ROM(PROM), electrically programmable ROM (EPROM), electrically erasable ROM(EEPROM), or flash memory. Volatile memory can include random accessmemory (RAM), which acts as external cache memory. By way ofillustration and not limitation, RAM is available in many forms such assynchronous RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM),double data rate SDRAM (DDR SDRAM), enhanced SDRAM (ESDRAM), SynchlinkDRAM (SLDRAM), and direct Rambus RAM (DRRAM). Additionally, thedisclosed memory components of systems or methods herein are intended tocomprise, without being limited to comprising, these and any othersuitable types of memory.

The illustrated aspects of the disclosure can be practiced indistributed computing environments where certain tasks are performed byremote processing devices that are linked through a communicationsnetwork. In a distributed computing environment, program modules can belocated in both local and remote memory storage devices.

The systems and processes described above can be embodied withinhardware, such as a single integrated circuit (IC) chip, multiple ICs,an application specific integrated circuit (ASIC), or the like. Further,the order in which some or all of the process blocks appear in eachprocess should not be deemed limiting. Rather, it should be understoodthat some of the process blocks can be executed in a variety of ordersthat are not all of which may be explicitly illustrated herein.

As used in this application, the terms “component,” “module,” “system,”“interface,” “cluster,” “server,” “node,” or the like are generallyintended to refer to a computer-related entity, either hardware, acombination of hardware and software, software, or software in executionor an entity related to an operational machine with one or more specificfunctionalities. For example, a component can be, but is not limited tobeing, a process running on a processor, a processor, an object, anexecutable, a thread of execution, computer-executable instruction(s), aprogram, and/or a computer. By way of illustration, both an applicationrunning on a controller and the controller can be a component. One ormore components may reside within a process and/or thread of executionand a component may be localized on one computer and/or distributedbetween two or more computers. As another example, an interface caninclude input/output (I/O) components as well as associated processor,application, and/or API components.

Furthermore, the terms “user,” “consumer,” “client,” and the like areemployed interchangeably throughout the subject specification, unlesscontext warrants particular distinction(s) among the terms. It is notedthat such terms can refer to human entities or automatedcomponents/devices supported through artificial intelligence (e.g., acapacity to make inference based on complex mathematical formalisms),which can provide simulated vision, sound recognition and so forth.

Further, the various embodiments can be implemented as a method,apparatus, or article of manufacture using standard programming and/orengineering techniques to produce software, firmware, hardware, or anycombination thereof to control a computer to implement one or moreaspects of the disclosed subject matter. An article of manufacture canencompass a computer program accessible from any computer-readabledevice or computer-readable storage/communications media. For example,computer readable storage media can include but are not limited tomagnetic storage devices (e.g., hard disk, floppy disk, magnetic strips. . . ), optical disks (e.g., compact disk (CD), digital versatile disk(DVD) . . . ), smart cards, and flash memory devices (e.g., card, stick,key drive . . . ). Of course, those skilled in the art will recognizemany modifications can be made to this configuration without departingfrom the scope or spirit of the various embodiments.

Artificial intelligence based systems, e.g., utilizing explicitly and/orimplicitly trained classifiers, can be employed in connection withperforming inference and/or probabilistic determinations and/orstatistical-based determinations as in accordance with one or moreaspects of the disclosed subject matter as described herein. Forexample, an artificial intelligence system can be used to dynamicallyperform operations as described herein.

A classifier can be a function that maps an input attribute vector,x=(x1, x2, x3, x4, xn), to a confidence that the input belongs to aclass, that is, f(x)=confidence (class). Such classification can employa probabilistic and/or statistical-based analysis (e.g., factoring intothe analysis utilities and costs) to infer an action that a user desiresto be automatically performed. In the case of communication systems, forexample, attributes can be information received from access points,servers, components of a wireless communication network, etc., and theclasses can be categories or areas of interest (e.g., levels ofpriorities). A support vector machine is an example of a classifier thatcan be employed. The support vector machine operates by finding ahypersurface in the space of possible inputs, which the hypersurfaceattempts to split the triggering criteria from the non-triggeringevents. Intuitively, this makes the classification correct for testingdata that is near, but not identical to training data. Other directedand undirected model classification approaches include, e.g., naïveBayes, Bayesian networks, decision trees, neural networks, fuzzy logicmodels, and probabilistic classification models providing differentpatterns of independence can be employed. Classification as used hereincan also be inclusive of statistical regression that is utilized todevelop models of priority.

In accordance with various aspects of the subject specification,artificial intelligence based systems, components, etc. can employclassifiers that are explicitly trained, e.g., via a generic trainingdata, etc. as well as implicitly trained, e.g., via observingcharacteristics of communication equipment, e.g., a server, etc.,receiving reports from such communication equipment, receiving operatorpreferences, receiving historical information, receiving extrinsicinformation, etc. For example, support vector machines can be configuredvia a learning or training phase within a classifier constructor andfeature selection module. Thus, the classifier(s) can be used by anartificial intelligence system to automatically learn and perform anumber of functions.

In addition, the word “example” or “exemplary” is used herein to meanserving as an example, instance, or illustration. Any aspect or designdescribed herein as “exemplary” is not necessarily to be construed aspreferred or advantageous over other aspects or designs. Rather, use ofthe word exemplary is intended to present concepts in a concretefashion. As used in this application, the term “or” is intended to meanan inclusive “or” rather than an exclusive “or.” That is, unlessspecified otherwise, or clear from context, “X employs A or B” isintended to mean any of the natural inclusive permutations. That is, ifX employs A; X employs B; or X employs both A and B, then “X employs Aor B” is satisfied under any of the foregoing instances. In addition,the articles “a” and “an” as used in this application and the appendedclaims should generally be construed to mean “one or more” unlessspecified otherwise or clear from context to be directed to a singularform.

What has been described above includes examples of the presentspecification. It is, of course, not possible to describe everyconceivable combination of components or methods for purposes ofdescribing the present specification, but one of ordinary skill in theart may recognize that many further combinations and permutations of thepresent specification are possible. Accordingly, the presentspecification is intended to embrace all such alterations, modificationsand variations that fall within the spirit and scope of the appendedclaims. Furthermore, to the extent that the term “includes” is used ineither the detailed description or the claims, such term is intended tobe inclusive in a manner similar to the term “comprising” as“comprising” is interpreted when employed as a transitional word in aclaim.

What is claimed is:
 1. A system, comprising: a processor; and a memorythat stores executable instructions that, when executed by theprocessor, facilitate performance of operations, comprising: receiving arequest to update a protection set for a first coded chunk in responseto detecting deletion of a primary data chunk, wherein the first codedchunk and the primary data chunk are stored in a geographicallydistributed data storage system; generating a transformation data chunkutilizing a secondary data chunk stored in the geographicallydistributed data storage system; and generating a second coded chunkhaving an updated protection set that has been updated from theprotection set, wherein the second coded chunk is generated utilizingthe transformation data chunk and the first coded chunk.
 2. The systemof claim 1, wherein the operations further comprise updating the firstcoded chunk with the second coded chunk.
 3. The system of claim 2,wherein the operations further comprise deleting the first coded chunkand the transformation data chunk.
 4. The system of claim 1, wherein thegenerating the second coded chunk comprises using an XOR operation tocombine the transformation data chunk and the first coded chunk.
 5. Thesystem of claim 1, wherein the first coded chunk comprises a codedversion of the primary data chunk, and wherein the first coded chunk isa result of a Geo erasure coding.
 6. The system of claim 1, wherein thegeographically distributed data storage system utilizes a plurality ofzones for storing one or more chunks of data, and wherein the primarydata chunk is stored at a first zone, the secondary data chunk is storedat a second zone, and the first coded chunk is stored at a third zone.7. The system of claim 6, wherein the transformation data chunk isgenerated at the second zone.
 8. The system of claim 7, wherein theoperations further comprise: transforming the transformation data chunkfrom the second zone to the third zone.
 9. The system of claim 1,wherein the geographically distributed data storage system comprises acombined coded chunk generated using an XOR operation.
 10. A method,comprising: receiving, by a system comprising a processor and a memory,a request to update a protection set for a first coded chunk in responseto detecting deletion of a primary data chunk, wherein the first codedchunk and the primary data chunk are stored in a geographicallydistributed data storage system; generating, by the system, atransformation data chunk utilizing a secondary data chunk stored in thegeographically distributed data storage system; and generating, by thesystem, a second coded chunk having an updated protection set, whereinthe updated protection set is generated utilizing the transformationdata chunk.
 11. The method of claim 10, further comprising: updating, bythe system, the first coded chunk with the second coded chunk; anddeleting, by the system, the first coded chunk and the transformationdata chunk.
 12. The method of claim 10, wherein the geographicallydistributed data storage system utilizes zones for storage of one ormore chunks of data, and wherein the primary data chunk is stored at afirst zone of the zones, the secondary data chunk is stored at a secondzone of the zones, and the first coded chunk is stored at a third zoneof the zones.
 13. The method of claim 12, wherein the transformationdata chunk is generated at the second zone.
 14. The method of claim 13,further comprising: transforming, by the system, the transformation datachunk from the second zone to the third zone; and updating, by thesystem, the first coded chunk with the second coded chunk; and deleting,by the system, the first coded chunk and the transformation data chunk.15. The method of claim 10, wherein the generating the second codedchunk comprises using an XOR operation to combine the transformationdata chunk and the first coded chunk, wherein the first coded chunkcomprises a coded version of the primary data chunk, wherein the firstcoded chunk is result of a Geo erasure coding, and wherein thegeographically distributed data storage system comprises a combinedcoded chunk generated using the XOR operation.
 16. A machine-readablestorage medium, comprising executable instructions that, when executedby a processor, facilitate performance of operations, comprising:receiving a request to update a protection set for a first coded chunkin response to detecting deletion of a primary data chunk, wherein thefirst coded chunk and the primary data chunk are stored in ageographically distributed data storage system; generating atransformation data chunk utilizing a secondary data chunk stored in thegeographically distributed data storage system; generating a secondcoded chunk having an updated protection set; and updating the firstcoded chunk with the second coded chunk.
 17. The machine-readablestorage medium of claim 16, wherein the updated protection set isgenerated utilizing the transformation data chunk and from theprotection set.
 18. The machine-readable storage medium of claim 16,wherein the geographically distributed data storage system utilizes agroup of zones to store one or more chunks of data, wherein the primarydata chunk is stored at a first zone of the group of zones, thesecondary data chunk is stored at a second zone of the group of zones,the first coded chunk is stored at a third zone of the group of zones,and wherein the transformation data chunk is generated at the secondzone.
 19. The machine-readable storage medium of claim 18, wherein theoperations further comprise: transforming the transformation data chunkfrom the second zone to the third zone; and deleting the first codedchunk and the transformation data chunk.
 20. The machine-readablestorage medium of claim 16, wherein the generating the second codedchunk comprises using an XOR operation to combine the transformationdata chunk and the first coded chunk, wherein the first coded chunkcomprises a coded version of the primary data chunk, wherein the firstcoded chunk is result of a Geo erasure coding, and wherein thegeographically distributed data storage system comprises a combinedcoded chunk generated using the XOR operation.